Journal of Water and Soil Conservation
Year:2017 | Volume:24 | Issue:2|Papers Count:18

Background and Objectives: In recent decades following the massive increase in computational power, considerable progress has been made in hydrological models. As the complexity of the model increases, model parameters increases and this lead to increasing the chances of overfitting and difficulty in identifying both model parameter values and model structure. One possible way to mitigate over-parameterization/non-identifiability is reducing the number of parameters to a small number that can be sufficiently calibrated with limited data.Sensitivity analysis (SA) is a commonly used approach for identifying important parameters that dominate model behaviors. Overall, they can be categorized into two groups: local SA and global SA. The local SA explores the changes of model response by varying one parameter while keeping other parameters constant. On the other hand, the global SA examines the changes of model response by varying all parameters at the same time. No general rule has yet been defined for verifying the convergence of the General SA methods. In order to fill this gap this paper presents a convergence analysis of three widely used SA methods (Morris screening, Sobol and Entropy index) for two rainfall-runoff models, TOPMODEL and HBV. The simulations are carried out over ChehlChay watershed within Gorganrood River Basin.Materials and Methods: The sensitivity and interaction analysis based onSobol, Morris screen and Entropy methods were applied. The Morris method has been proposed as a screening method to identify a subset of inputs that have the greatest influence on the outputs.Sobol SA is a global, variance-based method that attributes variance in the model output to individual parameters and their interactions.Mutual entropy analysis is a sensitivity analysis method in which the mutual entropy of two variables is regarded as the correlative extent between these two variables. The distribution character of data (X, Y) can be expressed by contingency tables.The HBV model and TOPMODEL are used as a test problem. There are thirteen and nine parameters in the HBV model and TOPMODEL models, respectively. In each model, samples of the model parameter space are obtained using a latin-hypercube. The convergence analysis has been performed by increasing the number of simulations until there was no significant change of the sensitivity measure. In addition, the three SA methods are evaluated and compared in terms of convergence, the related evolution of the parameter ranking results and required computation cost.Results: Results of the quantitative convergence analysis for Morris screen was achieved at 700 and 1000 number of simulations for HBV and TOPMODEL models, respectively. Results for the Sobol method deviated considerably from the other methods by 22000 and 28000 for the TOPMODEL and HBV models, respectively. In Entropy method need about 6000 samples for the same purpose in both hydrological models. The ranking of parameters sensitivity indices in TOPMODEL for the first two most sensitive parameters for the three methods are similar. In general, the ranks of sensitive parameters are the same for all methods. Meanwhile for Entropymethod, M and Srmax as the third and fourth ranking are vice versa than other two methods.In HBV model, Sobol and Morris screen methods provide similar results for those model parameters having the highest influence. For the parameter P, the sensitivity obtained from Entropy method was 3rd rank but in two other methods the parameter ranking varies from 3rd to sixth. In Entropy parameter FC becomes the most important parameter but in Morris screen and Sobol methods, the model parameter BETA selected as the parameter with the highest importance.Conclusion: There is no single best strategy for all problems. Therefore in general use of two or more methods, preferably with dissimilar theoretical foundations, may be needed to increase confidence in the ranking of the key inputs.This study conducted a comprehensive evaluation of the effectiveness and efficiency of three SA methods by using the HBV and TOPMODEL models as test problem. The strengths and limitations of qualitative and quantitative SA methods are explored.For the Sobol method, a comparatively large number of simulations (>20 000) were required to sufficiently cover the parameter space. Hence, performing Sobol method for complex models is often becoming problematic. The Morris method, instead, is computationally cheap and needed only<1000 simulations to obtain stable results.

Background and Objectives: With the emergence of computers and geographic information system (GIS), as well as access to spatial digital data, different methods of data mining, modeling and estimation of soil properties found their place in soil sciences. Data mining of soil properties using computer-based statistical methods uncovers hidden patterns in the database which ultimately leads to the fitness of a model for estimation of soil properties. These methods can be used in the scorpan equation. Two main components of scorpan model include environmental variables and learning program. In the present study, three different methods including multiple linear regression (MLR), artificial neural network (ANN) and Gene Expression Programming (GEP) as “f’ function in scorpan model were evaluated and compared in estimating of soil properties using auxiliary data such as vegetation data, topography and remote sensing data.Material and Methods: The study area with an area of 1225 ha was located in Bajgiran rangelands, Khorasan Razavi province, Iran. In order to investigate vegetation cover and soil 137 units were investigated in which 3-5 plots were selected with a distance of 10 meters apart along an accidental transect and plant species names and numbers besides vegetation percentage were recorded. Next, one soil sample was taken from each transect (Totally 137 soil sample). Train attributes derived from digital elevation model; different bands derived from the ETM and used for computing spectral indices; and plant diversity indices were calculated using Simpson and Shannon-Wiener. These obtained parameters were used as covariate in estimating calcium carbonate equivalent, clay, density, nitrogen, carbon, sand, silt and saturated moisture capacity. Data deduction was done by PCA analysis to deduct the number of input data for ANN and GEP models and finally, Normalization and standardization were carried out on the data.Results: The results obtained from the evaluation of three numerical methods based on root mean square error (RMSE), mean bias error (MBE) and coefficient of determination (R2) showed that ANN model had the highest accuracy in estimating soil properties, given the higher coefficients of determination for calcium carbonate equivalent, clay, density, nitrogen, carbon, sand, silt and saturated moisture capacity with the values of 0.72, 0.46, 0.69, 0.67, 0.77, 0.62, 0.7 and 0.85, respectively, moreover, lower RMSE with the values of 7.46, 4.46, 0.08, 0.03, 0.27, 5.6, 3.5 and 3.4, respectively. ANN could explain 60-85 percent of variability of soil properties, among which the best estimates were for saturated moisture capacity and soil organic carbon with R2=0.85 and R2=0.77, respectively.Conclusion: Evaluating the estimation of soil properties through three numerical models introduced ANN as the most accurate model. ANN validation results showed that mean bias error (MBE) for estimated soil properties were close to zero and this confirms that the fitting has been created unbiased by model. Furthermore, the low RMSE of model verified accurate estimation of soil variables. The results also indicate that GEP had higher accuracy than the linear regression method for most soil properties.

Background and Objectives: Groundwater pollution is a complex and full of uncertainty process, on a regional scale. Development of an integrated method for assessing groundwater vulnerability, can be efficient in order to optimized management and protection of them. Because of fertile soil and sufficient water resources, Ramhormoz plain is suitable area for agriculture that by development of agriculture, use of chemical fertilizers and pesticide, this plain always is at risk of contamination. One of the suitable approach to prevent groundwater contamination, identify areas of potential contamination. The aim of this study is to produce vulnerability map of Ramhormoz plain alluvial aquifer using DRASTIC model and then use artificial intelligence techniques to improve the results of the DRASTIC model. Due to the importance of groundwater resources in the study area that are used for various purposes including agriculture, Aquifer vulnerability study and protect these areas for development and management of water resources is essential.Materials and Methods: In this study, first, vulnerability evaluation of Ramhormoz alluvial aquifer plain was performed using DRASTIC model and in the following, artificial intelligence methods was used to optimize the model. DRASTIC model includes the following parameters: depth to water table, net recharge, aquifer media, soil media, topography, impact of vadose zone and hydraulic conductivity that are effective in groundwater vulnerability assessment. This method, based on the standard weights of DRASTIC model and obtained layers for each of the seven parameters, calculates the amount of aquifer vulnerability. After preparation of the layers, vulnerability of Ramhormoz alluvial aquifer plain was determined using drastic model. Also the groundwater vulnerability map and DRASTIC index was calculated for the entire area. In order to evaluation of accuracy of the obtained results from the model, nitrate concentration data existing in groundwater have been used for verification. Following In order to improve results, DRASTIC model was integrated by artificial neural networks, fuzzy logic (Sugeno and Mamdani) and Adaptive Neuro-Fuzzy Inference System methods and four vulnerability maps was obtained using different models of artificial intelligence.Results: The groundwater vulnerability map toward the contamination was prepared by the division into three vulnerability ranges including low, medium and high and DRASTIC index was calculated for the entire area between 48 and 156. Correlation coefficient 0.97 between DRASTIC index and nitrate concentration reflects the relatively good accuracy of this method. Also, the results of the implementation of these models showed that the used artificial intelligence models have the ability to improve the primary DRASTIC model results. By comparing the results of the models can be concluded that the Adaptive Neuro-Fuzzy Inference System model has the best result.Conclusion: The determination coefficient, R2, for the Adaptive Neuro-Fuzzy Inference System, neural networks and Mamdani fuzzy and Sugeno fuzzy models, is 0.99, 0.94, 0.98 and 0.87 respectively.According to the final model, South- Southeast regions have the highest potential for contamination.

Background and Objectives: Splash erosion is recognized as the first stage in a soil erosion process and results from the soil surface bombing by rain drops. Splash erosion is a complex process including the detachment of soil particles by raindrops followed by splash transport of a part of the detached particles.Quantification of splash erosion in the soils with different textures for various combinations of rainfall intensities and antecedent moisture content (AMC) is essential to understand splash erosion processes.The investigation on the splash erosion in the field is often expensive and time-consuming. Rainfall simulation has been used extensively as a cost effective method for soil erosion prediction across a lot of related factors. This study was conducted to investigate splash erosion in relation to rainfall intensity and AMC in different soil textures using the simulated rainfalls.Materials and Methods: Splash erosion was measured in three soil textural classes (sand, silt and clay) and four AMC (from air-dried to saturation conditions) using the four simulated rainfalls (10, 20, 30 and 40 mm h-1 in intensity). Forty-eight experimental units were designed at three replicates and analyzed using the factorial experiment in the completely randomized design. The experimental units were splash boxes with 25 cm × 35 cm dimensions and 5-cm depth. Splash erosion was determined using the accumulation of splashed particles during each rainfall and accordingly drying in 105 °C for 24-h. The physicochemical soil properties were determined using the conventional methods in the laboratory.Splash erosion data were analyzed using the Duncan parametric test for comparison of the effects of soil texture, rainfall intensity and, AMC on the splash erosion. Data were analyzed using the SAS 9.4 software and the diagrams were delineated using the Sigma Plot software.Results: Significant differences were found in the splash erosion among the soil textures (P<0.001), AMC (P<0.001) and rainfall intensity (P<0.001). Silt showed the highest splash erosion (average value 257.2 g/m2) which was related to easy detachment of silt particles and readily transport by returned raindrops.Sand was the most resistant soil texture to splash erosion. Splash erosion in sand soil varied from 35.43 to 152.70 g per m2. There were significant differences interactions between soil texture and rainfall intensity (P<0.001), soil texture and AMC (P<0.001), rainfall intensity and AMC (P<0.001). Splash erosion was positively affected by the rainfall intensity. Silt showed the highest susceptibility the splash erosion with increasing rainfall intensity. Different results were observed for AMC among the soil textures in the splash erosion. With an increase in AMC, splash erosion in the silt significantly increased, while clay showed a negative trend with increasing AMC. Sand didn’t show an obvious difference in the splash erosion with increasing AMC. Splash erosion was significantly affected by the interactions of three variables (soil texture, rainfall intensity and AMC). The highest splash (441.20 g per m2) erosion was observed in Silt for AMC with 50% saturated point under the rainfall intensity of 40 mm h-1 Sand showed the lowest splash (35.43 g per m2) erosion for AMC with 5% saturated point under 10 mm h-1 rainfall intensity.Conclusion: Results of this study indicated that Silt is the most susceptible soil texture to splash erosion.Also, variations of splash erosion in silt texture were larger than other textures. Splash erosion of each soil could be reliably predicted based on the rainfall intensity and antecedent water content.

Background and Objectives: Construction and development of irrigation and drainage networks in downstream of dams is a very important infrastructural project and its execution could enhance water use efficiency in agricultural activities, especially in water scarcity and drought condition. But, we cannot neglect their unwanted social and environmental side effects. Even, some social and environmental disadvantages of such projects are more than their advantages and may lead to social dissatisfaction.Regarding current drought, water scarcity, and low surface water use efficiency in Korbal plain of Doroodzan dam downstream in Fars province, Regional Water Organization has tried to develop irrigation and drainage networks. Whereas, impact assessment of every project which is executed in natural context in order to enhance its benefits and diminish its disadvantages is quite necessary, investigating farmers appraisal towards irrigation networks development project in downstream of Doroodzan dam was the main objective of this research.Materials and Methods: This study was a descriptive-analytical, non-experimental and applied research and survey technique was used to collect data. Statistical population was all those farmers whom have been covered by the project (1029 farmers). Based on two stages random sampling method, 269 beneficiaries were selected as sample group. In first stage four dikes (Amir, Feysabad, Tilakan and Mavan) were considered. Then in second stage, phase of the project (social and participation study phase, execution phase and construction phase) for each dike were considered. After that, all villages classified towards those characteristics and finally sample farmers selected from each phase and each dike, randomly. Questionnaire was data collection instrument and its face validity was confirmed by a panel of relevant experts and a pilot study was done to determine its reliability. The Cronbach's alpha coefficient was between 0.54-0.91 Results: According to findings, most of beneficiaries appraised environmental, social and economic impacts of modern irrigation and drainage networks in mediate and desirable level. Besides, findings revealed that some moderate variables of the research had significant effect on the project impact assessment. Based on the causal model which proposed in this study, four attitudinal variables have had direct and indirect effect on the dependent variable. The results of path analysis showed that among those four attitudinal variables, farmers, attitude toward construction of irrigation canals, attitude toward the future of agricultural activities, and their attitude toward the water price had the most direct causal effect on the project impact assessment as dependent variable, respectively. Social participation had the greatest direct influence on dependent variable among the other variables.Conclusion: According to path analyses results, it can be concluded those beneficiaries who had more social participation, more contribution in local decision- making, more crop under cultivation, had more positive attitude towards canals construction, and had more positive attitude towards future of agricultural activities and water current price, and those who were elder, have evaluated the project impacts more positively.

Background and Objectives: The limits of precipitation in any area, is said to be abnormal rainfall that is on the trail and away from the focus point of the distribution of rainfall. The high limits and high sequence distribution of precipitation have been of interest recently. In this regard, according to the geographical features of the area, many and varied threshold for this feature is introduced and applied. One of the most widely used indexes of daily precipitation is based on generalized distribution of limit values. The aim of this study was to determine the threshold of extreme rainfall in the western regions of Iran (Hamedan, Lorestan, Kordestan, Kermanshah and Ilam) and spatial analysis thresholds.Materials and Methods: For this purpose, data from rainfall of 69 synoptic stations and climatology in a 50-year period (1961 to 2010) with the distribution of general extreme value and non-parametric method (index percentile, 95th and 99th) of threshold rainfall were selected for sapacial analysis through two climatological criteria. In this study, three distribution test limit values generalized POT (test MRL, TC, DI) nonparametric test, procedure CPOT that the average threshold of these three non-parametric methods and also the parametric method was applied (Indexes of 95th percentile and the 99th percentile have been selected for the threshold Extreme rainfall of the Western Country. And finally, using GIS to analyze the spatial distribution thresholds determined by the methods mentioned in the stations studied were discussed.Results: The results of the evaluation showed that CPOT is a good way to choose the threshold of extreme precipitation of Western Iran that the 81 percent threshold Extreme rainfall stations studied in the given amounts fall in between both criteria and the lowest amount is estimated by 95th percentile which is generally non-parametric method according to both evaluation criteria that the first criterion related to the data series above the threshold and the other is selected in the threshold value, did not show satisfactory results. Threshold Extreme rainfall less than half the number of stations studied fell at the borders of both criteria.Conclusion: The results of the analysis of parametric methods (some generalized distribution) and nonparametric on 69 stations showed that Extreme rainfall threshold of most of the stations was between 22 to 26 mm and CPOT method is a proven and efficient method for determining the threshold of extreme precipitation in Western country and also MRL is a satisfactory method for selecting threshold extreme precipitation.

Background and Objectives: Paddy Fields Development and Renovation Project changes infrastructures of the rice farm management and converts traditional plot the plot irrigation system to water delivery management, which provides access to irrigation canals and drainage for each paddy plot. Even though many years have passed from the start of implementation of the project in northern provinces and several researchers have pointed fundamental problems out in the water distribution system of the project, but most previous studies have qualitative basis and the analysis is mainly based on the satisfaction of farmers or empirical judgments of experts in different parts of the project and until now less quantitative analysis has been provided on the basis of key performance indicators such as reliability indicating that ensure the delivery of agricultural water on time, to the extent necessary and for the time required and criteria such as dependability, steadiness, timeliness and predictability of the delivery of water provided by the researchers for its evaluation. Such indicators can measure the effectiveness of the system and finally it possible to provide planning, redesign and implementation of the corrective operation.Materials and Methods: In this study, reliability indices including the variability and predictability of water delivery system were calculated and compared for two concrete and earthen irrigation canals and the plots that are covered by them in renovated paddy fields of Esmaelkola village in Joybar city of Mazandaran province.Results: The results of the quantitative indicators evaluation shows that although concrete lining of canal has made noticeable effect on the promotion of variability indicators in earthen channel, as Concrete channels have shown better results than earthen channel in the values of these parameters: Adequacy and dependability indices, respectively, 18 and 5 percent, fifty percent level of delivery reliability as 0.14, timeliness of water delivery as much as 4 days and delivery steadiness index as 0.27, but structural and managerial problems in intake and control system leading to inadequate and inequitable distribution of water between plots of lined channel according to the coefficient of variation 0.33 for adequacy and 0.46 for reliability and timely variations of water delivery to downstream plots show a major difference with defined standards considering steadiness lower than 0.5, timeliness index that was mostly more than 10 days and low amount of fifty percent level of delivery reliability. Both earthen and concrete channels linear correlation was mostly reversed between the delivered and required volume of water that indicates the lack of water delivery management based on demand. The inverse correlation coefficient between the variables of water delivery is -0.97 for concrete lined channel, so, it is correctly predicted improper management of water delivery in the final decades and in the earthen channel, the value of 0.30 shows there is no correlation between the volume of delivered and required water and consequently low predictability of the system.Conclusion: Generally, even with the concrete canal lining, indicators of reliable water delivery are not favorable in comparison with standards of these criteria. On the one hand, traditional, experience-oriented and non-technical management system that governs water delivery in renovated farms has no appropriate scheduling for the use of supplied water during the planting season and on the other hand improving the existing system need to reform plots' intakes and flow control methods in the canal and complimentary water delivery schedule based on the irrigation demand.

Background and Objectives: The study of adsorption/desorption process for heavy metals in soil and the evaluation of how these are transferred or accumulated or what happens to them in layers of soil is an important issue, that has attracted the attention of many researchers. Ability of accumulated metal transfer in layers of soil, because of surface water infiltration, precipitation and even infiltration of municipal and industrial wastewater in soil on one hand and desorption of metals from soil as solution and their transfer and percolation into groundwater, which causes groundwater pollution, on the other hand are among other reasons which add to the importance of these types of research. Flow of raw wastewater in layers of soil due to adsorption/desorption process leads to transport of metals in soil column. This research was carried out as field operations, the aim of which was to assess desorption process for metals Ni, Zn and Pb that exist in soil in Semnan industrial region due to raw wastewater infiltration that are released from soil.Materials and Methods: After the region raw wastewater infiltration, changes of concentration of metals in soil layers were measured and a statistical assessment was carried out with data, then for infiltration of wastewater to be applied in soil a pit was excavated. Soil sampling from the lower layers of the infiltration pit was done and Samples depth was from 20 to 300 cm in different layers.Before infiltration of wastewater, samples from the lower depths of the infiltration pit was obtained and used for determining the initial concentration in the soil layers (pre-infiltration) and after infiltration of wastewater, amount of heavy metals concentrations in the same depths are considered as post-infiltration data. A statistical assessment was carried out for evaluating the effect of desorption process (a paired-samples T-test is used for comparison of means) for each metal in the total soil column. This assessment was conducted by using statistical package SPSS18.Results: The results indicate that, displacement in the center of mass happens from the top to the lower layers for the three metals. The statistical assessment indicated in this soil column, desorption process of Ni from soil to wastewater solution was effective, but for metals Zn and Pb was not.Transport ratio was calculated and for Ni, Zn and Pb were 136, 21 and 10, respectively. Dissolved concentration was calculated for Ni, Zn and Pb at the end of soil column were 4.07, 1.95 and 1.25 (ppm), respectively.Conclusion: Wastewater infiltration leads to transfer of all of metals towards more depths in soil column. Ni percolates into the groundwater much faster than other metals. The order obtained from metals affected by desorption process and amount of percolation into ground water was Ni>Zn>Pb.

Background and Objectives: Wind erosion is known as one of land degradation aspects in arid and semiarid regions. This type of erosion leads to loss of soil organic carbon and nutrients and consequently results in soil quality decline and reduction in plant growth and production. Soil moisture affects the erosion rate through controlling threshold velocity and soil erodibility. This study was done to investigate the effect of initial soil moisture content on wind erosion rate and threshold velocity as well in two soils with different texture classes using a wind tunnel facility under controlled conditions.Materials and Methods: The experiment was conducted in two separate tests on two soils with different texture classes, each as factorial based on completely randomized design. Two factors including wind speed and initial moisture each at three replications were applied for each soil. For this purpose, two soils with different texture classes of sandy loam and sandy were chosen, afterwards various levels of initial moisture were produced for each soil and then were exposed to several wind speeds. Regarding to the different texture and erosion threshold of the soils, three levels of initial moisture contents of 1.5, 6.5 and 11.5% for sandy loam and 1, 2.5 and 4.5% for sandy soil were produced. After preparing the soil samples and placing in the wind tunnel, wind velocities of 5, 7.5 and 10 m s–1 at 10 cm height were generated and finally, sediment yield due to wind erosion was measured. In addition, the threshold wind velocity was determined through the observation method. Furthermore, the critical moisture content for each soil was determined based on the minimum moisture amount in which a significant reduction in erosion rate was observed. To assess the influences of wind speeds and moisture contents on erosion rate, relative change percentage was calculated for both the soils.Results: Results of this study showed that with increasing wind speed and initial moisture content, wind erosion rates increased and decreased, respectively. The measured erosion rates for sandy loam and sandy soils ranged from 0.015 to 0.768 and 0.086 to 14.088 g m–2 min–1, this difference was attributed to the soils primary and secondary particle size distribution. With increasing the soils moisture content, the threshold wind velocity increased as a power function. The critical moisture contents of 6.5% and 4.5% were determined for sandy loam and sandy soils, respectively. With increasing moisture content in sandy loam soil from 1.5 to 6.5%, at wind velocities of 5, 7.5 and 10 m s–1, the erosion rate decreased by 64.6, 80.7 and 62.9%, while with increasing moisture content from 1.5 to 11.5%, it was reduced by 82.3, 90.8 and 77.5%, respectively. These reduction values for sandy soil for the increase in moisture from 1 to 1.5% were 27.7, 32.8 and 71.3% and for the increase in moisture content from 1 to 4.5% were 92.2, 86.6 and 93.9%, respectively.Conclusion: The findings of this research revealed the importance of maintaining and or increasing in soil moisture to combat wind erosion, so that due to soil moisture increase, wind erosion rate can be restricted by 90%. It was concluded that the critical value of moisture content differs in various soils. This critical value for sandy soil (4.5%) was lower than that in sandy loam soil (6.5%). The results also indicated that both primary and secondary particle size distribution have undeniable impacts on wind erosion rate through affecting on moisture retention, aggregate density, inter-particles cohesion and threshold velocity. Finally, it was found that by reducing wind speed toward values less than the threshold velocity, in addition to soil management strategies to maintain and improve soil moisture, wind erosion can be reduced, remarkably.

Background and Objectives: An increasing need to water causes the importance of planning management in order to control water consumption in the future. River flow prediction, in addition to the management of water resources, can predict natural disasters such as flood and drought. Therefore, an accurate estimation of river flow using different models is an issue which has been considered by different water resource researchers. Intelligent models have been used to predict river flow. One of these models, which have shown appropriate performance, is Gene Expression Programming (GEP). A use of intelligent models in combinations has been lately accepted and for this purpose, the wavelet transform is usually used.Materials and Methods: In this study, the GEP model was used for modeling flow in the daily and monthly scale in Gamasiyab River. For this purpose, data of precipitation, temperature, evaporation and flow Gamasiyab River in Varayeneh Station was used during the period from 1970 to 2012. To increase the accuracy of the model, two methods of data pre-process, called Wavelet transform and principal components analysis (PCA) and were used in such a way that the primary signal of each input parameter was decomposed using the wavelet transform.Then, to determine main sub-signals, the principal components analysis was used and main sub-signals as inputs were entered into the GEP model to produce Wavelet-Gene Expression Programming (WGEP).Results: Detection of different structures of the GEP model showed that the performance of the model was good on the daily scale, but in the monthly scale, the performance was reduced. The comparison of the WGEP model with The GEP model showed that the performance of the hybrid model in both of the daily and monthly scale was better than the simple model. It’s because of a pre-process which was done on data. The results of the hybrid model, based on the coefficient determination, was increased by 4% on the daily scale and by 23% in the monthly scale. Also, regarding too many sub-signals, using the Principal Components Analysis increased the speed of running.Conclusion: Using pre-process of data has increased the performance of the model and using the PCA, as an auxiliary tool for the wavelet transform, increased the speed and accuracy of the model. Totally, the results showed that it’s possible to use the GEP model with the wavelet transform as a suitable tool for modeling and predicting the flow of Gamasiyab River.

Background and Objectives: Environmental pollution by heavy metals has been known as a serious problem associated with industrialization. Due to high stability nature, heavy metals could be accumulated in soils at toxic levels and insert to human food chain. The total concentration of heavy metals can indicate the extent of contamination, but is not usually an accurate indication of the bioavailability, mobility and phyto-toxicity and thus the fractionation procedures have been used to show environmental risks of toxic metals. Heavy metals in soils occurred in soluble, exchangeable, organically bound, oxides bound and residual fractions. There is limited information about bioavailability heavy metals in soils around coal washing factories of Iran.This study was conducted to investigate the distribution of chemical fractions of copper, lead and cadmium in a coal washing factory located in Zarand.Materials and Methods: The study area (Zarand coal washing plant) is located about 70 kilometers from Kerman city (Western Iran). A nested grid sampling scheme was adopted using Google Earth. In this study, 4 areas were selected according to dominant vegetation. Composite soil samples (5 samples per point) were systematically collected from 0 to 30 cm depth. Soil samples were air dried and passed through a 2 mm sieve. For determination of total concentration of heavy metals (Cu, Cd and pb), 20 mL of 5N HNO3 was added to 0.2 g of soil samples and heated for 10 minutes and then kept at room temperature for 24 h. after centrifuge, the concentration of heavy metals was determined using atomic absorption spectrometer. Chemical fractions of heavy metals including acid-soluble/exchangeable fraction, reducible (bound to Fe-Mn oxides), oxidizable (bound to organic matter) and residual fractions were sequentially extracted. After each successive extraction, separation was carried out by centrifugation at 3000 rpm for 30 min. the supernatant was filtered with Whatman 42 filter. The concentration of Cu, Cd and pb in supernatant was determined using atomic absorption spectrophotometer.Results: The results showed that the total contents of Cu, Pb and Cd in 4 areas was higher than the standard range provided by Iranian soil and water office of human environment Bureau, showing the serious pollution of studied heavy metals in soils. Based on Geoaccumulation Index (GI), site 4 were highly polluted by Pb whereas Cu and Cd were in non-polluted to slightly polluted status. Spatial distribution of heavy metals showed that the highest content of Cd, Pb and Cu were found in the northwest and the west direction of factory with agricultural land use showing the alarming status of this area. In all sites, the residual and exchangeable fractions of heavy metals had the greatest and lowest values among other fractions, respectively. The distribution of studied metals (Cu, Cd and Pb) were lined in the order of residual fraction>reducible fraction>oxidizable fraction>exchangeable fraction.Conclusion: According to average concentration presented by soil and water office of human environment Bureau, Cu, Pb and Cd values are in alarming status. The changes in chemical fractions of Cu and Pb following the order of residual>Reducible>Oxidizable fraction>exchangeable. Based on Geo-accumulation Index (GI), the areas were highly polluted by Pb. The results showed that in comparison with Cd and Cu, the main fraction of Pb is deposited in residual fraction in soil. Based on these results, the Cd and Cu are more dangerous than Pb in this region and are capable to transport in food chain.

Background and Objectives: Due to water resources shortage in our country, improvement of water distribution management is unavoidable matter for increase irrigation network performance. Control systems have an important role in water distribution irrigation network and network successful depends on performance. Successful modeling and running depends on tuning of control coefficients. Aim of this study is determination of optimal control coefficients using SCE method.Materials and Methods: In this study, PID controller (upstream control and downstream control) is developed for slide gate on the ICSS model. For tuning coefficients, SCE algorithm is used for increment and decrement operation scenario in Mc canal of Alborz irrigation network with 12.6 km length at 5 hr time operation. The objective function consists of three performance indexes of MAE (Maximum Absolute Error), IAE (Integral of Absolute Error) and dimensionless form of SRT (System Response Time). Also Molden and gates indexes is used for performance assessment canal.Results: Optimal coefficients controller are gained in operation scenario. Using gained coefficients, model will be able to tune water level in target level in increment and decrement process at short time. Maximum errors are related to C1 structure with 10 cm in upstream controller and C3 structure with 6 cm in downstream controller. Upstream controller are not able to tuning water level in downstream, so water supply in TO14 and TO16 is disturbed and MPA index is fair and poor performance classes Respectively for TO14 and TO16. The MPA index have been improved in downstream controller Compared to upstream controller. MPA, MPF, MPD indexes are good performance classes in both controller and MPE index is fair.Conclusion: Results show gained optimal coefficients of the developed model to the upstream and downstream controllers is Responsive to changes in operation in a short time.

Background and Objectives: Considering global warming as a prominent challenge in the world and based on increase and protection of soil carbon stock in forest ecosystems, optimum monitoring carbon sequestration in Forests is very efficient to examine an optimal forest management and climate change parameters in association with variation of soil carbon pool. Therefore, a comprehensive protocol is needed for developing models with high certainty in relation to soil organic carbon (SOC) stock. Using the models including comfortably measurable variables with the lowest cost inventory, protective controlling for carbon pool variations at different soil layers in forest ecosystems can be applicable.Materials and Methods: This research was conducted in Nour Forest Park as a largest plain forest in north of Iran. The number of 25 plots with 400 m2 was laid out at the three stands (Alder-Ironwood, Maple- ironwood, Elm-Hornbeam) based on randomized complete block design for measuring plant biodiversity indices and sampling soil carbon factor at two different soil depths (0-20 cm and 20-40 cm).Generally, a total of 75 plots were outlined in the forest. Moreover, four micro-plots with area of 1 m2 were nested in the center and corners of each plot for measuring ground vegetation coverage. Measuring the plant elements and sampling the soils in turns were carried out in summer and early of autumn. Regression analyses as and simulating the outputs by ANN was used for optimum monitoring soil carbon pool.Results: The results showed that multiple linear regression including the correlated plant diversity indices with the SOC stock in different soil depths were valid for estimating the response variables according to statistical issues such as Akaike information coefficient and variance inflation factor (VIF<10). However, the mentioned model was not a considerable predictor for the SOC stock in comparison with the other models. Considering the non-linear regression functions, S-curve model includingAbundance of herbal species was the best predictor for SOC at the soil top layer and log-transformed power model including species dominance (D) of trees, Abundance of and evenness (J') of ground vegetation was a highly accurate model for predicting the SOC at the soil mineral layer. Besides, using back propagation algorithm in the ANN indicated that the SOC stock was predicted with the highest accuracy through introducing matrix ofAbundance and J' with topology of one hidden layer and 15 neurons including function of Tan-sigmoid. Furthermore, the SOC stock in the soil mineral layer was predicted with the highest accuracy by adding layer of D to previous matrix input in the network with topology of two hidden layers and 35 neurons in each layer.Conclusion: Irrespective of ecological and biological interpretations, an accurate type of mathematic relationship (real function) between plant biodiversity indices and the studied response variable is dubious and complicated with marginal certainty and statistical issues such as variance inflation factor. Hence, ANN application can be a best alternative to traditional models for predicting the response variables.Subsequently, like the parameters in the traditional models, the topology of each model in ANN is determining the architecture and efficiency of monitoring the responses in different soil layers.

Background and Objectives: Infiltration is the most critical and often most difficult parameter for evaluation of surface irrigation systems. In particular, the infiltration specification is variable with time and place. In general, a fairly large number of field measurements is needed to show the average farm condition. The aim of this research is the investigation of the accuracy of extraction the type cumulative infiltration equation by using the Non-point methods and the adjusted by the irrigation process, in simulation of the closed end furrow irrigation system. For simulation, was used from the zero inertia model in WinSRFR software and the zero inertia and Hydrodynamic models in SIRMOD software.Materials and Methods: This research was implemented at two farms whose names were 201E and 201C1, in the Haft tape Cultivation and Industry of Sugarcane that Sugarcane was cultivated in furrows floor. In each farm 7 consecutive furrows selected. Even furrows test and odd furrows had buffer roles.The average furrows length was in 201C1 farm, 268 meters and in the 201E farm 165 meters. In the both farms Longitudinal slope of the test furrows was measured and 0.001 (meter/meter) obtained and furrows width, 1.5 meters. The furrows were irrigated by closed end method. In order to prepare the data for the advance and recession, was put the station in the furrows length intervals of 20 meters. In both farms, three irrigations were evaluated. For measurement of the inlet flow rate to the test furrows, was used from WSC flume, type 3. Kostiakov Louis type cumulative infiltration equations obtained by the inflow –outflow method for both farms. By using the Advance and recession data and the volume of inflow water and infiltration to the furrows the type cumulative infiltration equations was adjusted and the adjusted cumulative infiltration equations obtained for each furrow. Then the amounts of the advance of the each irrigation for both farms simulated by using the type cumulative infiltration equations and adjusted and the hydrodynamic and Zero inertia models of both WinSRFR and SIRMOD software.Results: Results of this research showed that placement the amount of infiltration experiments flow rate in SM software improves significantly the simulation process. Compare the results of the Zero inertia and hydrodynamic models of SM software shows that results of these models in simulation of the closed end furrow irrigation process with Sugarcane Cultivated in furrows floor, were similar and had little difference together. Evaluation of the result of SM and WS software simulations shows that if the type cumulative infiltration equations used in the advanced accuracy of process simulation in the 201C1 farm, had the good and moderate ranking and in the 201E farm, had the weak rank. Adjusting the infiltration equations and using them in these software upgrade accuracy simulation in the 201C1 farm to excellent ranking and in the 201E farm to the good and moderate range. This increase of accuracy was the improvement of the average of Relative Absolute Error index in the 201C1 farm 63 percent and in the 201E farm 53 percent. Results too showed that the SM software in simulated of both farms with the fewer Mean Square Error and the fewer Relative Absolute Error had better performance and both software have predicted the Computing advanced times more than the real amount them.Conclusion: In general results of this research shows that if the adjusted infiltration equations used Instead of the type infiltration equations in the designing, simulation and evaluation of the closed end furrow irrigation systems, increased the accuracy of results to significantly, so finally will cause the improvement and increasing of the irrigation systems hydraulic indexes.

Background and Objectives: River sediments are the major component of the aquatic ecosystems and play an important role in the nutrients cycle and contaminants transformation in river systems.Sediment particles are transported in the forms of the suspended and bed sediment depending on the river flow regime and the size distribution of the particles. Sediments in the river are in equilibrium with the pore water and river flow. Therefore, the composition of sediments strongly affects water quality and the biological activities in the aquatic systems. Release of the organic and inorganic contaminants and nutrients from the sediments to the river flow is mainly influenced by the physical and chemical properties of the sediments. Thus, understanding of the basic physical and chemical properties of river sediments is essential for sustainable management of the watershed. The aim of this study was evaluate and compare the physical and chemical properties of the suspended and bed sediments of the Roze-Chay river in the Urmia region.Materials and Methods: Total of the 19 bed sediments were collected along the river. Bed sediments were sampled from three parts of the river including up-stream (6 samples), mid-stream (6 samples) and down-stream (7 samples). In addition, six suspended sediments were sampled from the river during a flood event. Sediment samples were passed through a 2000 micron sieve and were analyzed for their basic physical and chemical properties. Hierarchical cluster analysis and principle component analysis were preformed for grouping the sediment samples and identifying the most effective properties of them.Results: Results indicated that the sand and silt particles are very dominant in bed and suspended sediments, respectively. The average silt and very fine sand content in bed sediments were 15.8 and 15.5 percents, while the silt and very fine sand particles content in suspended sediments were 44 and 25 percent, respectively. However, bed sediment have coarse texture due to their higher sand content in comparison with suspended sediments. The average values of organic matter and electrical conductivity of bed sediments were 1.7 and 2.5 times greater than the suspended samples. The organic matter content in up-stream bed sediments were higher than the middle and downstream parts, which may due to the discharge of the domestic sewage in this part of the watershed. Principle component and the hierarchical cluster analysis showed that the organic matter, EC and particle size distribution are the most effective properties of the sediments.Conclusion: Discharge of the domestic sewage to the river bed may has led to the accumulation of the organic matter and soluble salts in the bed sediments of the upstream part. As a result, the basic physical and chemical properties of the upstream bed sediments are different from the middle and downstream parts. Preventing the entry of the sewage into the river bed especially at the upstream part has an essential role in sustainable management of the Roze-chay river ecosystem. Multivariate analysis of the sediment samples revealed that there was a significant difference between the properties of the suspended and bed sediments.

Background and Objectives: Fire is the most important disturbance factor in forest ecosystems that can result in short and long term changes in soil physical and chemical properties. The changes of these properties in soil after fire may have negative effects on forest ecosystem even in long term. Since the fire frequency in Zagros forests have been increasing in the recent years, identifying the short term and long term effects of fire on soil properties in these forests is necessary to prevent soil degradation. Hence, in this study the short and long term responses of some physical and chemical properties of soil were investigated in order to identify the recovery time of these properties.Materials and Methods: In order to investigate the recovery time of soil physical and chemical properties after fire, 3 places in one site (distance about 1km from each other) in Zagros forests were selected with different times of fire occurrence including: 1, 3 and 10 years after fire. To decrease the environmental effects, we considered a separate unburnt control plot for each place in their adjacent and each place was compared with its own control plot. The soil sampling was performed randomly from the depth of 0-20 cm with 4 replications. A total of 24 composite soil samples were collected. Several soil physical and chemical properties were measured including: pH, EC, CEC, organic carbon (OC), nitrogen (N), phosphorus (P), saturated water content, bulk density (BD), C/N ratio and soil texture. The statistical analysis of experiment data was performed using IBM SPSS software and mean comparison was done by t test method.Results: The results showed that soil pH, CEC, EC and P were significantly increased 1 year after fire. Soil pH and CEC were recovered to the pre-fire level in treatments 3 and 10 years after fire, while, EC and P were significantly decreased compared to their control. Saturate water of soil was decreased 1 year after fire however, no significant difference was observed compared to the pre-fire level after 3 and 10 years. Results indicated that OC and N were significantly decreased in all the times after fire and they were not recovered to the pre-fire level even after 10 years. BD was decreased 1 and 3 years after fire however, after 10 years no significant difference was observed compared to the control. No significant difference was in soil C/N ratio, clay, sand and silt compared to the control in any times after fire.Conclusion: It was concluded that some physical and chemical properties of soil may recovered in short time however; some others may not have recovered even 10 years after fire. Soil OC, N and P are of those properties that need long time to be recovered.

Background and Objectives: With increasing restrictions on water resources, the use of wastewater in agriculture as a source of unconventional water and the only sustainable source of water, was expanded, especially in arid and semi-arid regions. The aim of this study was to examine the possibility of using wastewater of Shahrekordʼs municipal sewage treatment plant for agriculture irrigation.Materials and Methods: For this purpose, some of physical, chemical and microbial parameters of wastewater quality of Shahrekordʼs municipal sewage treatment plant, in April-September 2015, were measured on a monthly basis and then compared with the standards of Iranian Environmental Protection Organization, World Health Organization (WHO) and World Food and Agricultural Organization (FAO).Results: According to the results of water quality, the average amount of fecal and total coliforms in wastewater during the study, were 6416.8 and 16966.7 (MPN (100 ml)-1), respectively; that was outside of the recommended permissible range by the Iranian environmental protection organization standards for using wastewater in agriculture, so more chlorination is necessary before wastewater discharge. In addition, based on the average value of microbial parameters, fecal coliform and the number of intestinal nematodes (0 N (100 ml)-1) and according to World Health Organization standards, the use of wastewater for irrigation of plants that can be eaten raw, is not possible. Also according to FAO standard, wastewater application in terms of average amount of bicarbonate concentration in this period (4.64 me L-1), had low to moderate limitation for crops.Conclusion: The wastewater of municipal sewage treatment plant in Shahrekord can be used for irrigation of cereal and industrial crops resistant to high concentrations of bicarbonate.